Multicollinearity: Why Occur and How to Remove
Multicollinearity, a term that often sends shivers down the spines of statisticians and data scientists, is a phenomenon encountered in regression analysis where two or more predictor variables in a multiple regression model are highly correlated. While correlation itself isn’t inherently bad, high multicollinearity can wreak havoc on your model’s interpretation and performance, leading to … Read more